Peter Uhlenberg. 2009. International Handbook of Population Aging. Heidelberg: Springer-Verlag.
Bibliographic record
Abstract
It is remarkable, as Peter Uhlenberg observes in the opening lines of this edited collection, that The Study of Population (Hauser and Duncan 1959) had no chapter on aging, and the words "population aging" did not even appear in the index.In effect, the 1950s and early 1960s, as a baby boom period, was a time when some populations were getting younger rather than aging, and the concern related more to population growth.We learn from the chapter by Donald Rowland that the number of aged did not increase appreciably for sixty years or more after the start of the mortality decline, and that in pre-transition societies typically not more than 3 per cent of persons reached their 65th birthdays.How different has been the population change since the 1970s, and this marked contrast with past population patterns will only be accentuated in the coming decades.Using the cut-off of 10 per cent aged 65+, and based only on countries with a million or more persons, there were 9 countries with older populations in 1950, compared to 26 in 1975, 41 in 2000, 64 in 2025, and 105 in 2050.In 2000, Canada is 31st in rank order from the oldest, but in 2025 Canada is 22nd on the list, with 20.7 per cent aged 65+ compared to 28.9 per cent in Japan as the oldest population.This is a very comprehensive collection, with 34 chapters bringing a wealth of material to bear on the topic.While not present in every chapter, the themes of international comparisons and of life course provide further unity to the text, as does the strong historical context.From a policy perspective, the unifying element is that aging is not to be viewed as a crisis, but there are profound implications, both challenges and opportunities, and the considerations associated with the deep policy challenges (e.g., labour force renewal, social security, health costs) go much beyond the demographics.As an example, the cross-national comparisons of health care costs find little correlation with the proportion of the population that is aged 65 and over (p.628).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".